AMR Country Hotspots

##  Family: zero_inflated_poisson 
##   Links: mu = log; zi = logit 
## Formula: n_amr_events ~ ln_livestock_consumption_kg_per_capita + ln_migrant_pop_perc + ln_tourism_inbound_perc + ab_export_perc + health_expend_perc + human_consumption_ddd + english_spoken + ln_pubs_sum_per_capita + ln_promed_mentions_per_capita + ln_gdp_per_capita + offset(ln_population) 
##          zi ~ ln_pubs_sum_per_capita + ln_promed_mentions_per_capita + ln_gdp_per_capita + ln_population + english_spoken
##    Data: data[[i]] (Number of observations: 199) 
## Samples: 120 chains, each with iter = 2000; warmup = 1000; thin = 1;
##          total post-warmup samples = 120000
## 
## Population-Level Effects: 
##                                        Estimate Est.Error l-95% CI
## Intercept                                -14.11      2.70   -19.64
## zi_Intercept                              25.22      6.29    13.37
## ln_livestock_consumption_kg_per_capita    -0.40      0.19    -0.68
## ln_migrant_pop_perc                        0.17      0.07     0.06
## ln_tourism_inbound_perc                    0.19      0.14    -0.05
## ab_export_perc                             3.88      1.86    -0.30
## health_expend_perc                        -0.01      0.03    -0.06
## human_consumption_ddd                      0.11      0.02     0.06
## english_spoken                            -0.17      0.14    -0.44
## ln_pubs_sum_per_capita                     0.14      0.12    -0.09
## ln_promed_mentions_per_capita              0.27      0.08     0.11
## ln_gdp_per_capita                          0.01      0.11    -0.18
## zi_ln_pubs_sum_per_capita                 -0.10      0.29    -0.69
## zi_ln_promed_mentions_per_capita           0.00      0.32    -0.63
## zi_ln_gdp_per_capita                      -1.11      0.27    -1.67
## zi_ln_population                          -1.00      0.22    -1.45
## zi_english_spoken                         -0.44      0.47    -1.38
##                                        u-95% CI Eff.Sample Rhat
## Intercept                                 -9.26         80 2.02
## zi_Intercept                              38.07      11666 1.01
## ln_livestock_consumption_kg_per_capita    -0.07         62 5.59
## ln_migrant_pop_perc                        0.33         74 2.31
## ln_tourism_inbound_perc                    0.50         64 3.91
## ab_export_perc                             6.72         76 2.20
## health_expend_perc                         0.06         70 2.62
## human_consumption_ddd                      0.16         67 3.06
## english_spoken                             0.10         78 2.08
## ln_pubs_sum_per_capita                     0.37         95 1.65
## ln_promed_mentions_per_capita              0.43         85 1.86
## ln_gdp_per_capita                          0.29         79 2.06
## zi_ln_pubs_sum_per_capita                  0.45       1444 1.03
## zi_ln_promed_mentions_per_capita           0.65     109779 1.00
## zi_ln_gdp_per_capita                      -0.60       2290 1.02
## zi_ln_population                          -0.58       1486 1.03
## zi_english_spoken                          0.48       6899 1.01
## 
## Samples were drawn using sampling(NUTS). For each parameter, Eff.Sample 
## is a crude measure of effective sample size, and Rhat is the potential 
## scale reduction factor on split chains (at convergence, Rhat = 1).

## [1] TRUE